mcutils/xray/example_main_tiox.py

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from __future__ import print_function,division
import numpy as np
import pylab as plt
import mcutils as mc
import mcutils.xray as xray
from mcutils.xray import id9
id9 = xray.id9
# use npz files (they can handle more stuff (list of arrays,unicode) than h5py)
id9.default_extension = '.npz'
#id9.default_extension = '.h5'
def readCalc():
fold = "../tiox/calculated_patterns/"
names = "alpha beta lam".split()
fnames = "alpha500K beta290K lambda".split()
calc = dict()
for name,fname in zip(names,fnames):
q,i=np.loadtxt(fold + "%s.xye.q"%fname,unpack=True)
calc[name] = xray.storage.DataStorage( dict( q=q, i=i ) )
return xray.storage.DataStorage(calc)
calc = readCalc()
def azav(folder,nQ=1500,force=False,saveChi=True,mask=470):
if isinstance(mask,int):
files = xray.utils.getFiles(folder,"*.edf*")
img = xray.azav.read(files[0])
temp = np.ones_like(img,dtype=bool)
temp[:mask] = False
mask = temp
return id9.doFolder_azav(folder,nQ=nQ,force=force,mask=mask,saveChi=saveChi)
def datared(folder,monitor=(1,5),showPlot=True,**kw):
data,diffs = id9.doFolder_dataRed(folder,monitor=monitor,**kw)
if showPlot:
xray.utils.plotdiffs(diffs.q,diffs.data,t=diffs.scan,
absSignal=diffs.dataAbsAvAll,absSignalScale=30)
plt.plot(calc.lam.q,calc.lam.i/1000+0.1,label='calc')
plt.title(folder + " norm %s" % str(monitor))
return data,diffs
def doall(folder,force=False):
azav(folder,force=force)
return datared(folder)
def anaAmplitue(run=6):
fname = "../tiox/tiox1/run%d/diffs.npz" % run
data = xray.storage.DataStorage(fname)
ranges = ( (1.75,1.85), (2.2,2.4), (3.25,3.4) )
nPlot = len(ranges)
fig,ax = plt.subplots(nPlot,1,sharex=True)
for r,a in zip(ranges,ax):
idx = (data.q>r[0]) & (data.q<r[1])
amplitude = np.abs(data.data[:,idx]).mean(axis=1)
a.plot(data.scan,amplitude,'-o')
a.set_title("Range %s"%(str(r)))
def plotCalc(scale=1):
fold = "../tiox/calculated_patterns/"
q,i=readtxt(fold + "alpha500K.xye.q")
plt.plot(q,i*scale,label="alpha")
q,i=readtxt(fold + "beta290K.xye.q")
plt.plot(q,i*scale,label="beta")
q,i=readtxt(fold + "lambda.xye.q")
plt.plot(q,i*scale,label="lambda")